U.S. patent application number 16/120985 was filed with the patent office on 2019-08-08 for lung sound monitoring device and lung sound monitoring method thereof.
This patent application is currently assigned to Industrial Technology Research Institute. The applicant listed for this patent is Industrial Technology Research Institute. Invention is credited to Cheng-Li CHANG, Ho-Hsin LEE, Yi-Fei LUO, Chun-Fu YEH.
Application Number | 20190239819 16/120985 |
Document ID | / |
Family ID | 65804075 |
Filed Date | 2019-08-08 |
![](/patent/app/20190239819/US20190239819A1-20190808-D00000.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00001.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00002.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00003.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00004.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00005.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00006.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00007.png)
![](/patent/app/20190239819/US20190239819A1-20190808-D00008.png)
![](/patent/app/20190239819/US20190239819A1-20190808-M00001.png)
![](/patent/app/20190239819/US20190239819A1-20190808-M00002.png)
View All Diagrams
United States Patent
Application |
20190239819 |
Kind Code |
A1 |
CHANG; Cheng-Li ; et
al. |
August 8, 2019 |
LUNG SOUND MONITORING DEVICE AND LUNG SOUND MONITORING METHOD
THEREOF
Abstract
A lung sound monitoring device is provided. The lung sound
monitoring device includes an acoustic sensor and a processor. The
acoustic sensor is configured to capture the chest cavity sound of
a subject at a first monitoring position on the subject and convert
the chest cavity sound into a first chest cavity sound signal. The
processor is configured to receive the first chest cavity sound
signal and perform a filter process to obtain a first lung sound
signal, and convert the first lung sound signal into a first lung
sound spectrum using time-domain frequency-domain conversion. The
processor acquires a first intensity index according to the first
lung sound spectrum, and outputs a prompt signal according to the
first intensity index to indicate whether the first monitoring
position is a qualified monitoring position.
Inventors: |
CHANG; Cheng-Li; (Hsinchu
City, TW) ; LUO; Yi-Fei; (Zhudong Township, TW)
; LEE; Ho-Hsin; (Hsinchu City, TW) ; YEH;
Chun-Fu; (Xingang Township, TW) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Industrial Technology Research Institute |
Hsinchu |
|
TW |
|
|
Assignee: |
Industrial Technology Research
Institute
Hsinchu
TW
|
Family ID: |
65804075 |
Appl. No.: |
16/120985 |
Filed: |
September 4, 2018 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
62626928 |
Feb 6, 2018 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G10L 25/18 20130101;
A61B 5/08 20130101; A61B 5/7257 20130101; A61B 2562/0204 20130101;
A61B 5/74 20130101; G10L 25/66 20130101; A61B 7/003 20130101; A61B
5/6823 20130101; A61B 5/7225 20130101; G10L 25/48 20130101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61B 7/00 20060101 A61B007/00; A61B 5/08 20060101
A61B005/08; G10L 25/66 20060101 G10L025/66; G10L 25/18 20060101
G10L025/18 |
Foreign Application Data
Date |
Code |
Application Number |
Mar 21, 2018 |
TW |
107109623 |
Claims
1. A lung sound monitoring device, comprising: an acoustic sensor,
for capturing a chest cavity sound of a subject at a first
monitoring position on the subject and converting the chest cavity
sound into a first chest cavity sound signal; and a processor, for
receiving the first chest cavity sound signal and performing a
filter process to obtain a first lung sound signal, and converting
the first lung sound signal into a first lung sound spectrum using
time-domain frequency-domain conversion; wherein the processor
acquires a first intensity index according to the first lung sound
spectrum, and outputs a prompt signal according to the first
intensity index to indicate whether the first monitoring position
is a qualified monitoring position.
2. The lung sound monitoring device as claimed in claim 1, wherein
the processor generates the prompt signal according to whether the
first intensity index exceeds a threshold; when the first intensity
index does not exceed the threshold, the prompt signal is a
movement instruction signal to indicate that the lung sound
monitoring device needs to be moved to a second monitoring position
on the subject; when the first intensity index exceeds the
threshold, the prompt signal is a positioning-completion signal,
and the lung sound monitoring device starts to record the lung
sound of the subject.
3. The lung sound monitoring device as claimed in claim 2, wherein
after outputting the movement instruction signal and moving the
lung sound monitoring device to the second monitoring position on
the subject, the acoustic sensor captures the chest cavity sound of
the subject at the second monitoring position and converts the
chest cavity sound into a second chest cavity sound signal; the
processor receives the second chest cavity sound signal and
performs the filter process to obtain a second lung sound signal,
and converts the second lung sound signal into a second lung sound
spectrum using time-domain frequency-domain conversion; the
processor acquires a second intensity index according to the second
lung sound spectrum; the processor further compares the first
intensity index and the second intensity index to determine whether
the first monitoring position or the second monitoring position is
a suitable lung sound monitoring position.
4. The lung sound monitoring device as claimed in claim 1, wherein
the processor further performs a pre-amplification process and a
pre-emphasis process after receiving the first chest cavity sound
signal.
5. The lung sound monitoring device as claimed in claim 1, wherein
before converting the first lung sound signal using time-domain
frequency-domain conversion, the processor retrieves a time segment
of the first lung sound signal, and the time segment has a time
length at least equal to one respiratory cycle of the subject.
6. The lung sound monitoring device as claimed in claim 1, wherein
the first intensity index is calculated by an equation, as
indicated below: Intensity index = .intg. a b amplitude ( x ) dx
.intg. 0 n amplitude ( x ) dx , ##EQU00002## wherein a is lower
limit of a preset lung sound frequency band; b is upper limit of
the preset lung sound frequency band; n is upper limit of the first
lung sound spectrum; x is a frequency of the first lung sound
signal; amplitude(x) is the intensity of the first lung sound
spectrum.
7. The lung sound monitoring device as claimed in claim 6, wherein
before calculating the first intensity index, the processor further
determines whether to use a selected lung sound frequency band, and
when the selected lung sound frequency band is used, setting lower
limit and upper limit of the selected lung sound frequency band as
values of a and b in the equation of the first intensity index.
8. The lung sound monitoring device as claimed in claim 3, wherein
the first intensity index is derived from a peak value of main
frequency in the first lung sound spectrum, and the second
intensity index is derived from the peak value of the main
frequency in the second lung sound spectrum.
9. The lung sound monitoring device as claimed in claim 1, further
comprising a prompt output device, configured to output the prompt
signal, wherein the prompt signal is presented as vibration, sound,
light signal or a combination thereof.
10. The lung sound monitoring device as claimed in claim 1, further
comprising a transmission device, configured to transmit the first
chest cavity sound signal, the first lung sound signal or the first
intensity index to a storage device or a cloud server for
subsequent recording, monitoring or analysis.
11. A lung sound monitoring method for a lung sound monitoring
device which comprises an acoustic sensor and a processor, the
method comprising: capturing a chest cavity sound of a subject at a
first monitoring position on the subject by the acoustic sensor and
converting the chest cavity sound into a first chest cavity sound
signal; receiving the first chest cavity sound signal using the
processor and performing a filter process to obtain a first lung
sound signal, and converting the first lung sound signal into a
first lung sound spectrum using time-domain frequency-domain
conversion; acquiring a first intensity index by the processor
according to the first lung sound spectrum, and outputting a prompt
signal according to the first intensity index to indicate whether
the first monitoring position is a qualified monitoring
position.
12. The lung sound monitoring method as claimed in claim 11,
wherein the processor generates the prompt signal according to
whether the first intensity index exceeds a threshold; when the
first intensity index does not exceed the threshold, the prompt
signal is a movement instruction signal to indicate that the lung
sound monitoring device needs to be moved to a second monitoring
position on the subject; when the first intensity index exceeds the
threshold, prompt signal is a positioning-completion signal, and
the lung sound monitoring device starts to record the lung sound of
the subject.
13. The lung sound monitoring method as claimed in claim 12,
wherein after outputting the movement instruction signal and moving
the lung sound monitoring device to the second monitoring position
on the subject, the acoustic sensor captures the chest cavity sound
of the subject at the second monitoring position and converts the
chest cavity sound into a second chest cavity sound signal; the
processor receives the second chest cavity sound signal and
performs the filter process to obtain a second lung sound signal,
and converts the second lung sound signal into a second lung sound
spectrum using time-domain frequency-domain conversion; the
processor acquires a second intensity index according to the second
lung sound spectrum; the processor further compares the first
intensity index and the second intensity index to determine whether
the first monitoring position or the second monitoring position is
a suitable lung sound monitoring position.
14. The lung sound monitoring method as claimed in claim 11,
further comprising using the processor to perform a
pre-amplification process and a pre-emphasis process after
receiving the first chest cavity sound signal.
15. The lung sound monitoring method as claimed in claim 11,
wherein before converting the first lung sound signal using
time-domain frequency-domain conversion, the processor retrieves a
time segment of the first lung sound signal, and the time segment
has a time length at least equal to one respiratory cycle of the
subject.
16. The lung sound monitoring method as claimed in claim 11,
wherein the first intensity index is calculated by the equation
below: Intensity index = .intg. a b amplitude ( x ) dx .intg. 0 n
amplitude ( x ) dx , ##EQU00003## wherein a is the lower limit of
the preset lung sound frequency band; b is the upper limit of the
preset lung sound frequency band; n is the upper limit of the lung
sound spectrum; x is the frequency of the first lung sound signal;
amplitude(x) is the intensity of the first lung sound spectrum.
17. The lung sound monitoring method as claimed in claim 16,
wherein before calculating the first intensity index, the processor
further determines whether to use a selected lung sound frequency
band, and when the selected lung sound frequency band is used,
setting the lower limit and the upper limit of the selected lung
sound frequency band as values of a and b in the equation of the
first intensity index.
18. The lung sound monitoring method as claimed in claim 13,
wherein the first intensity index is derived from a peak value of
main frequency in the first lung sound spectrum, and the second
intensity index is derived from the peak value of the main
frequency in the second lung sound spectrum.
19. The lung sound monitoring method as claimed in claim 11,
wherein the lung sound monitoring device further comprises a prompt
output device, and the method further comprises outputting the
prompt signal by the prompt output device, wherein the prompt
signal is presented as a vibration, a sound, a light signal, or a
combination thereof.
20. The lung sound monitoring method as claimed in claim 11,
wherein the lung sound monitoring device further comprises a
transmission device, and the method further comprises transmitting
the first chest cavity sound signal, the first lung sound signal or
the first intensity index via the transmission device to a storage
device or a cloud server for subsequent recording, monitoring or
analysis.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This Application claims priority of Taiwan Patent
Application No. 107109623, filed on Mar. 21, 2018, the entirety of
which is incorporated by reference herein. Furthermore, this
application claims the benefit of U.S. Provisional Application No.
62/626,928 filed on Feb. 6, 2018, the entirety of which is
incorporated by reference herein.
BACKGROUND
Field of the Disclosure
[0002] The present disclosure relates to a lung sound monitoring
device, and relates to a lung sound monitoring device and a lung
sound monitoring method that can assist in determining the suitable
position of capturing lung sound.
Description of the Related Art
[0003] At present, the diagnosis of pulmonary obstruction in
patients is accomplished through auscultation by an experienced
clinician. The clinician must personally hold a stethoscope and
make a diagnosis that draws upon his personal experience after
carefully auscultating several specific sites on the patient's
chest. Therefore, breathing sounds are an important basis for
judging the physiological condition of the lungs.
[0004] However, patients with symptoms such as Chronic Obstructive
Pulmonary Disease (COPD) often have weaker breath sounds due to
pulmonary obstruction. When recording a lung sound, the stethoscope
must be accurately placed between the ribs in a specific position,
and it is not easy to obtain a good capturing position in
operation. Moreover, continuous monitoring of lung sounds for
follow-up condition tracking and analysis is very much needed by
respiratory intensive care units, but there is currently no
physiological monitor capable of continuously recording lung
sounds.
SUMMARY
[0005] A detailed description is given in the following embodiments
with reference to the accompanying drawings.
[0006] The present disclosure provides a lung sound monitoring
device, comprising an acoustic sensor and a processor. The acoustic
sensor is configured to capture the chest cavity sound of a subject
at a first monitoring position on the subject and convert the chest
cavity sound into a first chest cavity sound signal. The processor
is configured to receive the first chest cavity sound signal and
perform a filter process to obtain a first lung sound signal, and
convert the first lung sound signal into a first lung sound
spectrum using time-domain frequency-domain conversion. The
processor acquires a first intensity index according to the first
lung sound spectrum, and outputs a prompt signal according to the
first intensity index to indicate whether the first monitoring
position is a qualified monitoring position.
[0007] The present disclosure further provides a lung sound
monitoring device, wherein the processor generates the prompt
signal according to whether the first intensity index exceeds a
threshold; when the first intensity index does not exceed the
threshold, the prompt signal is a movement instruction signal to
indicate that the lung sound monitoring device needs to be moved to
a second monitoring position on the subject; when the first
intensity index exceeds the threshold, the prompt signal is a
positioning-completion signal, and the lung sound monitoring device
starts to record the lung sound of the subject. After outputting
the movement instruction signal and the lung sound monitoring
device moving to the second monitoring position on the subject, the
acoustic sensor captures the chest cavity sound of the subject at
the second monitoring position and converts the chest cavity sound
into a second chest cavity sound signal. The processor receives the
second chest cavity sound signal and performs the filter process to
obtain a second lung sound signal, and converts the second lung
sound signal into a second lung sound spectrum using time-domain
frequency-domain conversion; the processor acquiring a second
intensity index according to the second lung sound spectrum. The
processor further compares the first intensity index and the second
intensity index to determine whether the first monitoring position
or the second monitoring position is a suitable lung sound
monitoring position.
[0008] The present disclosure also provides a lung sound monitoring
method for a lung sound monitoring device which comprises an
acoustic sensor and a processor, the method comprising capturing
the chest cavity sound of a subject at a first monitoring position
on the subject by the acoustic sensor and converting the chest
cavity sound into a first chest cavity sound signal; receiving the
first chest cavity sound signal by the processor and performing a
filter process to obtain a first lung sound signal, and converting
the first lung sound signal into a first lung sound spectrum using
time-domain frequency-domain conversion; acquiring a first
intensity index according to the first lung sound spectrum by the
processor, and outputting a prompt signal according to the first
intensity index to indicate whether the first monitoring position
is a qualified monitoring position.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] The present disclosure can be more fully understood by
reading the subsequent detailed description and examples with
references made to the accompanying drawings, wherein:
[0010] FIG. 1 is a schematic diagram of a lung sound monitoring
device according to an embodiment of the present disclosure.
[0011] FIG. 2 is a block diagram of the main circuit portion of the
lung sound monitoring device shown in FIG. 1.
[0012] FIG. 3A is a flowchart of a lung sound monitoring method
according to an embodiment of the present disclosure.
[0013] FIG. 3B and FIG. 3C are schematic diagrams before and after
the pre-emphasis process according to an embodiment of the present
disclosure.
[0014] FIG. 3D is another embodiment of the lung sound monitoring
method shown in FIG. 3A.
[0015] FIG. 4A and FIG. 4B are schematic diagrams of a lung sound
spectrum according to an embodiment of the present disclosure.
[0016] FIG. 5 is a flowchart of a lung sound monitoring method
according to another embodiment of the present disclosure.
[0017] FIG. 6 is a schematic diagram of a calculation intensity
index according to another embodiment of the present
disclosure.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0018] The following description is of the best-contemplated mode
of carrying out the disclosure. This description is made for the
purpose of illustrating the general principles of the disclosure
and should not be taken in a limiting sense. The scope of the
disclosure is best determined by reference to the appended
claims.
[0019] FIG. 1 is a schematic diagram of a lung sound monitoring
device 100 according to an embodiment of the present disclosure.
FIG. 1 is a schematic cross-sectional view of a lung sound
monitoring device 100. The lung sound monitoring device 100
includes an attachment suction cup 101, a sound collection chamber
102, a main circuit portion 103, and a prompt output device 104.
The attachment suction cup 101 may be a soft material sucker or
adhesive for attaching to the subject's body and adapting to
different body shapes. The lung sound monitoring device 100 is
attached to the thoracic cavity (chest cavity) of the subject's
chest or back using the attachment suction cup 101. The sound
collection chamber 102 may be a cavity formed of a light and rigid
material, such as a titanium alloy single material or a composite
material coated with a metal film on the surface of the plastic
material. The attachment suction cup 101 is attached to the
subject, and a sealed cavity is formed with the attaching surface
of the subject. The sound collection chamber 102 cooperates with
the main circuit portion 103 to capture the chest cavity sound of
the subject. The main circuit portion 103 may include a microphone,
a processor, and other circuits for collecting the chest cavity
sound of the subject and performing subsequent data analysis. The
main circuit portion 103 further includes a prompt output device
104. The prompt output device 104 may output a signal such as a
sound, a light signal, or a vibration to alert the subject or the
medical care assistant so that they can determine whether the
position of the lung sound monitoring device 100 is a good one with
which to capture the chest cavity sound.
[0020] FIG. 2 is a block diagram of the main circuit portion of the
lung sound monitoring device 100 shown in FIG. 1. As shown in FIG.
2, the main circuit portion 200 includes an acoustic sensor 201, a
processor 202, a prompt output device 203, a transmission device
204, a memory 205, and a power device 206. The acoustic sensor 201
may be an omnidirectional, unidirectional, or bi-directional
microphone, and the present disclosure is not limited thereto. In
this embodiment, the acoustic sensor 201 captures the chest cavity
sound of the subject at a first monitoring position on the subject
and converts the chest cavity sound into a first chest cavity sound
signal. The processor 202 may be a central processing unit (CPU), a
microcontroller (MCU), an application-specific integrated circuit
(ASIC), or the like, and the present disclosure is not limited
thereto. The processor 202 is electrically connected to the
acoustic sensor 201, receives the first chest cavity sound signal,
and performs the preceding signal processing to obtain the first
lung sound signal of the lung sound of the subject. Then, the
processor 202 converts the time domain of the lung sound signal of
the subject into the frequency domain to obtain the first lung
sound spectrum. The processor 202 calculates the first intensity
index, and outputs a prompt signal according to the first intensity
index to indicate whether the first monitoring position is a
qualified monitoring position. The chest sound signal captured from
the above-mentioned qualified monitoring position where the lung
sound monitoring device located is clinically sufficient to
represent the lung sound of the subject, and can be used to assist
the professional medical care assistant to diagnose or analyze the
disease condition of the subject. The detailed process flow of the
processor 202 will be described later within FIGS. 3A-3D.
[0021] The prompt output device 203 may include a speaker, a light
bulb, an LED lamp, a vibrator, or a combination thereof. The prompt
output device 203 is configured to receive the prompt signal sent
by the processor 202, wherein the prompt signal is generated by the
prompt output device 203 in the form of vibration, sound, light
signal, or a combination thereof. The prompt output device 203
outputs a prompt signal to let the subject or medical care
assistant know whether the current monitoring position of the lung
sound monitoring device 100 is a qualified (good) monitoring
position. For example, the prompt output device 203 can output a
voice through the speaker that can instruct the subject or medical
care assistant to move the lung sound monitoring device 100 to the
second monitoring position to capture another chest cavity sound.
Or indicate that the first monitoring position is a qualified
(good) monitoring position, and the lung sound monitoring device
100 can continuously record the chest cavity sound using the
acoustic sensor 201. In another embodiment, the prompt output
device 203 can also display the intensity of the first intensity
index calculated by the processor 202 in a long strip through a
plurality of light bulbs, or the prompt output device 203 can
display different colors such as red, blue and green through a
light bulb to distinguish whether the monitoring position is a
qualified monitoring position. Similarly, the prompt output device
203 can also indicate the strength of the first intensity index
through the vibration intensity output by the vibrator, and the
present disclosure is not limited thereto.
[0022] In the present embodiment, the main circuit portion 200
further includes a transmission device 204. The transmission device
204 transmits data such as the first chest cavity sound signal, the
first lung sound signal or the first intensity index to a storage
device or a cloud server (not shown) through a wireless or wired
transmission for subsequent records, monitoring or analysis. In
addition, the transmission device 204 can also transmit the lung
sound data continuously recorded by the acoustic sensor 201 to the
above server or connect with the respiratory intensive care unit to
monitor and analyze the respiratory physiological information of
the subject in real time.
[0023] The main circuit portion 200 further includes a memory 205
and a power device 206. The memory 205 is used to store the
threshold of the intensity index and the information of the lung
sound signal, the lung sound spectrum and the intensity index
calculated by the processor 202 and the like. Therefore, the
processor 202 is enabled to compare data of different time
sequences and output a prompt signal. The power device 206 is used
to supply the power required by the lung sound monitoring device
100 to make it portable and wearable. In addition, the lung sound
monitoring device 100 may further include fasteners such as
bandages and straps (not shown) to allow the subject to fix the
lung sound monitoring device 100 in the chest position of the
subject, making it wearable.
[0024] Referring to FIG. 3A, FIG. 3A is a flowchart of a lung sound
monitoring method according to an embodiment of the present
disclosure, and the method is used for a lung sound monitoring
device 100. After the processor 202 of the lung sound monitoring
device 100 loads the execution program, the processor 202 has a
predetermined function and can operate the lung sound monitoring
method of the present disclosure. In step 301, the acoustic sensor
201 captures the first chest cavity sound of the subject in the
first monitoring position and converts it into a first chest cavity
sound signal. The acoustic sensor 201 can convert the first chest
cavity sound signal into a digital signal using an
analog-to-digital converter, and transmit it to the processor 202.
In step 302, the processor 202 receives the first chest cavity
sound signal from the acoustic sensor 201. In step 303, since the
strength of the chest cavity sound signal captured by the acoustic
sensor 201 (e.g., a microphone) is usually weak (usually lower than
about 20 mV), a pre-amplification process is performed by the
processer 202. In step 304, the processor 202 obtains a first lung
sound signal that substantially reflects the lung sound of the
subject. In one embodiment, the processor 202 performs a band-pass
filter process or drives a filter to obtain a signal in a primary
lung sound frequency band (e.g., 100-1000 Hz) and to filter out
interference from the subject's heart sounds and ambient
sounds.
[0025] Next, in step 305, the processor 202 performs a pre-emphasis
process. The pre-emphasis process operates based on the equation
(1) below, so as to compensate for a signal that has been damaged
during the filtering out of ambient sounds to obtain a better
signal-to-noise ratio. Here, equation (1) is an example and is not
limited to such pre-emphasis process.
Y.sub.i=X.sub.i-.alpha..times.X.sub.i-1 (1)
[0026] Wherein Yi is the output signal intensity; i is the time
point; .alpha. is the pre-emphasis factor; X.sub.i is the signal
intensity at the current time, and X.sub.i-1 is the signal
intensity of the previous time point. Referring to FIG. 3B and FIG.
3C, FIG. 3B and FIG. 3C are schematic diagrams before and after the
pre-emphasis process according to an embodiment of the present
disclosure. In FIG. 3B and FIG. 3C, the intensity units on the
vertical axis are the digitized results, and 0 is the normalized
intensity on the relative basis. FIG. 3B shows the first lung sound
signal before the pre-emphasis process, and FIG. 3C shows the first
lung sound signal after the pre-emphasis process. In FIG. 3B and
FIG. 3C, the horizontal axis represents time (unit: 1/4000 second),
and the vertical axis represents the signal intensity.
[0027] In step 306, the processor 202 retrieves a time segment of
the first lung sound signal to speed up subsequent data processing
and analysis. Wherein, the time segment has a time length and may
be set to at least one respiratory cycle (e.g., 3-5 seconds) of the
subject. In step 307, the processor 202 converts the first lung
sound signal into the first lung sound spectrum using time-domain
frequency-domain conversion, wherein the processor 202 may convert
the first lung sound signal into the first lung sound spectrum
using a Fast Fourier Transform (FFT), and the present disclosure is
not limited thereto. It should be noted that the method flow of the
embodiment of the present disclosure is exemplary, and the above
steps 303 to 306 are not used to limit the implementation order. A
person skilled in the art of the present disclosure may adjust the
above steps according to actual need.
[0028] In step 308, the processor 202 calculates a first intensity
index according to the first lung sound spectrum. In the present
embodiment, the first intensity index is calculated by the
following equation (2).
Intensity index = .intg. a b amplitude ( x ) dx .intg. 0 n
amplitude ( x ) dx ( 2 ) ##EQU00001##
[0029] Wherein a is the lower limit of a preset lung sound
frequency band, b is the upper limit of the preset lung sound
frequency band, n is the upper limit of the first lung sound
spectrum, x is the frequency of lung sound signal, and amplitude
(x) is the intensity of the first lung sound spectrum. That is, the
intensity index is a ratio obtained by dividing the integral of the
intensity of the preset lung sound frequency band by the integral
of the intensity of the total lung sound spectrum in the frequency
domain. Furthermore, based on clinical experience, it is known that
the suitable preset range of the lung sound frequency band is 150
to 750 Hz, and the use of this range for the lung sound frequency
band can obtain more representative lung sound information.
Therefore, the values of a and b are 150 and 750 Hz, respectively.
The n value is the upper limit of the first lung sound spectrum,
i.e., the processor 202 obtains the upper limit of the frequency of
the main lung sound region after performing the filter process.
Generally, the n value is 1000 Hz.
[0030] Next, in step 309, the processor 202 outputs a prompt signal
according to the first intensity index to indicate whether the
first monitoring position is a qualified monitoring position.
Specifically, the processor 202 determines whether the first
intensity index exceeds a threshold and outputs a prompt signal.
The above threshold may be set to 0.75, but the present disclosure
is not limited thereto. When the processor 202 determines that the
first intensity index does not exceed (i.e., is less than or equal
to) the threshold, the first monitoring position is determined to
be a non-qualified monitoring position. In step 310, the output
prompt signal is a movement instruction signal to indicate that the
lung sound monitoring device 100 needs to be moved to a second
monitoring position on the subject. For example, the above movement
instruction signal may cooperate with the signal of the prompt
output device 203 and be displayed as a red light. The lung sound
monitoring device 100 may be moved by the subject himself or other
medical care assistant. Furthermore, since the lung sound signal is
monitored between the ribs of the subject's chest, the movement may
be a small distance, for example, 5 mm, but the present disclosure
is not limited thereto. In addition, the lung sound monitoring
device 100 may set a predetermined time for the subject or medical
care assistant to move to a new position. When the predetermined
time is over, the lung sound monitoring device 100 automatically
determines that it has been moved to the second monitoring
position. After moving to the second monitoring position, the lung
sound monitoring device 100 returns to step 301 and repeats step
302 to step 309 to recalculate the new intensity index and
determine whether new intensity index exceeds the threshold.
[0031] Returning to step 309, when the processor 202 determines
that the new intensity index exceeds the threshold, the current
monitoring position is determined to be a qualified monitoring
position. In step 311, the output prompt signal is a
positioning-completion signal. The lung sound monitoring device 100
records the lung sound of the subject using the acoustic sensor
201. For example, the positioning-completion signal may be matched
with the signal of the prompt output device 203 and displayed as a
green light. Furthermore, the data recorded by the lung sound
monitoring device 100 can be transmitted to the storage device or
server at the back end using the transmission device 204 for
subsequent recording, monitoring or analysis. In other embodiments,
the lung sound monitoring device 100 may also include a plurality
of acoustic sensors 201. Each acoustic sensor 201 is respectively
located at different monitoring positions and receives lung sounds
obtained from different monitoring positions at the same time. The
lung sound waveforms at different positions at the same time are
analyzed systematically.
[0032] Referring to FIG. 3D, FIG. 3D is another embodiment of the
lung sound monitoring method shown in FIG. 3A, which is used for
the lung sound monitoring device 100. In this embodiment, after the
lung sound monitoring method proceeds to step 307, the method
further includes step 3071. In step 3071, before calculating the
first intensity index, processor 202 determines whether to use a
selected lung sound frequency band. If used, in step 308, the lower
and upper limits of the selected lung sound frequency band are set
as the a value and the b value in the first intensity index
calculation equation. If not used, the method proceeds to step
3072, using a preset lung sound frequency band range (e.g., 150 to
750 Hz), and setting the preset lower limit and upper limit as the
a value and the b value in the first intensity index calculation
equation. It should be understood that whether or not to select
another lung sound frequency band of interest can be set in the
lung sound monitoring device 100 through the user interface under
the judgment of a medical professional.
[0033] Please refer to FIG. 4A and FIG. 4B. FIG. 4A and FIG. 4B are
schematic diagrams of a lung sound spectrum according to an
embodiment of the present disclosure. FIG. 4A and FIG. 4B show the
lung sound spectrums obtained from the lung sound signals captured
at different positions using the Fast Fourier Transform. FIG. 4A
shows the first lung sound spectrum obtained at the first
monitoring position, and the intensity index calculated by the
equation (2) is 0.6889. The processor 202 determines that the
intensity index does not exceed the threshold (the threshold is
assumed to be 0.75), and the lung sound monitoring device 100 needs
to be moved to the second monitoring position after the movement
instruction signal is output. FIG. 4B shows the second lung sound
spectrum obtained after moving to the second monitoring position.
After the calculation, the intensity index is 0.7573. The processor
202 determines that the intensity index exceeds the threshold and
sends the positioning-completion signal. The lung sound monitoring
device 100 starts to record the lung sound of the subject. In
addition, in the present embodiment, the selected lung sound
frequency band is not used, but the analysis is performed using the
preset lung sound frequency band. Therefore, the mark lines on the
left side and the right side in FIG. 4A and FIG. 4B are 150 and 700
hertz, respectively. In FIG. 4A and FIG. 4B, the horizontal axis
represents the frequency (unit: Hertz), and the vertical axis
represents the signal intensity.
[0034] FIG. 5 is a flowchart of a lung sound monitoring method
according to another embodiment of the present disclosure, which is
used for a lung sound monitoring device 100. The same steps in the
flowchart of the lung sound monitoring method shown in FIG. 5 and
FIG. 3A are also performed as described above, and will not be
described here. The main differences between FIG. 5 and FIG. 3A are
that in step 508, after the processor 202 calculates the first
intensity index, it outputs a prompt signal to indicate whether the
first monitoring position is a qualified monitoring position.
Wherein, the first intensity index can be calculated and obtained
according to equation (2). In addition, the processor 202 may
output the corresponding prompt signal according to whether the
first intensity index exceeds the threshold. In one embodiment,
when the first intensity index does not exceed the threshold, the
prompt signal is a movement instruction signal. The processor 202
outputs the movement instruction signal to indicate that the lung
sound monitoring device 100 needs to be moved to a second
monitoring position on the subject.
[0035] After the processor 202 outputs the prompt signal,
proceeding to step 509, the lung sound monitoring device 100 is
moved to a second monitoring position on the subject. The acoustic
sensor 201 captures the chest cavity sound of the subject at the
second monitoring position and converts into a second chest cavity
sound signal. Then, the processor 202 receives the second chest
sound signal and performs the filter process to obtain a second
lung sound signal that substantially reflects the lung sound of the
subject. The processor 202 converts the second lung sound signal
into the second lung sound spectrum using time-domain
frequency-domain conversion. The processor 202 calculates a second
intensity index based on the second lung sound spectrum. In brief,
step 501 to step 508 are repeated to calculate the second intensity
index.
[0036] In step 510, the processor 202 further compares the first
intensity index and the second intensity index to determine whether
the first monitoring position or the second monitoring position is
a suitable lung sound monitoring position. Furthermore, the
processor 202 may determine the first monitoring position or the
second monitoring position as the suitable lung sound monitoring
position according to the difference between the first intensity
index and the second intensity index, and update and output a new
prompt signal. The prompt output device 203 may output a
corresponding prompt signal after comparing the first intensity
index and the second intensity index. For example, the lung sound
monitoring device 100 may indicate the corresponding prompt signal
by the change of light signal or the level of vibration of the
prompt output device 203, or by displaying the intensity in a long
strip through the plurality of light signals. Through the above
steps, the lung sound monitoring device 100 may indicate the
subject or medical care assistant whether the current monitoring
position is a suitable lung sound monitoring position and may help
to determine a better lung sound receiving position. Furthermore,
the subject or medical care assistant may decide whether to
continue moving the monitoring position to obtain a better lung
sound monitoring position, and finally perform subsequent
recording, monitoring or analysis.
[0037] In another embodiment of the present disclosure, the
above-mentioned first intensity index and second intensity index
can be calculated in a different way. Please refer to FIG. 6. FIG.
6 is a schematic diagram of a calculation intensity index according
to another embodiment of the present disclosure. In detail, the
first intensity index and the second intensity index derived by the
processor 202 are peak values of the main frequency obtained in the
first lung sound spectrum and the second lung sound spectrum,
respectively. As shown in FIG. 6, the peak value of the main
frequency of the first lung sound spectrum obtained from the first
monitoring position is greater than the peak value of the main
frequency of the second lung sound spectrum obtained from the
second monitoring position. Therefore, the processor 202 determines
that the first monitoring position is a better monitoring position
than the second monitoring position and outputs a corresponding
prompt signal. In FIG. 6, the horizontal axis represents the
frequency (unit: Hertz), the vertical axis represents the amplitude
of the measured signal, and the vertical axis may also represent
the energy or intensity of the signal, but the present disclosure
is not limited thereto.
[0038] The lung sound monitoring device and the lung sound
monitoring method provided by the present disclosure may improve
upon the current state of diagnosis of pulmonary obstruction
patients, who need to be auscultated by an experienced clinician
personally holding a stethoscope, and according to personal
experience to achieve a good monitoring position. The lung sound
monitoring device and the lung sound monitoring method provided by
the present disclosure may help the subject or medical care
assistant to judge whether the lung sound monitoring device is in a
better lung sound receiving position. Furthermore, it provides a
function of continuous lung sound recording for subsequent
monitoring and analysis of the patient's condition.
[0039] Data transmission methods, or certain aspects or portions
thereof, may take the form of program code (i.e., executable
instructions) embodied in tangible media, such as floppy diskettes,
CD-ROMS, hard drives, or any other machine-readable storage medium,
wherein, when the program code is loaded into and executed by a
machine such as a computer, the machine thereby becomes an
apparatus for practicing the methods. The methods may also be
embodied in the form of program code transmitted over some
transmission medium, such as electrical wiring or cabling, through
fiber optics, or via any other form of transmission, wherein, when
the program code is received and loaded into and executed by a
machine such as a computer, the machine becomes an apparatus for
practicing the disclosed methods. When implemented on a
general-purpose processor, the program code combines with the
processor to provide a unique apparatus that operates analogously
to application-specific logic circuits.
[0040] While the disclosure has been described by way of example
and in terms of the suitable embodiments, it is to be understood
that the disclosure is not limited to the disclosed embodiments. On
the contrary, it is intended to cover various modifications and
similar arrangements (as would be apparent to those skilled in the
art). Therefore, the scope of the appended claims should be
accorded the broadest interpretation so as to encompass all such
modifications and similar arrangements.
* * * * *